code: def forward(self, hidden_states):
      if self.pool:
          hidden_states = hidden_states[:, 0]
      hidden_states = self.dense(hidden_states)
      hidden_states = self.act_fn(hidden_states)
      return hidden_states
  
file_path: allennlp/allennlp/modules/transformer/activation_layer.py
imports: from typing import Union
  import torch
  from allennlp.common import FromParams
  from allennlp.modules.transformer.transformer_module import TransformerModule
  from transformers.models.bert.modeling_bert import ACT2FN
label_desc: Use image node_id 3 for calling the ActivationLayer obj's underlying member method code with example usage: obj.forward(hidden_states) and returns: hidden_states